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Trajectory online adaption based on human motion prediction for teleoperation
journal contribution
posted on 2023-06-10, 00:53 authored by Jing Luo, Darong Huang, Yanan LiYanan Li, Chenguang YangIn this work, a human motion intention prediction method based on an autoregressive (AR) model for teleoperation is developed. Based on this method, the robot's motion trajectory can be updated in real time through updating the parameters of the AR model. In the teleoperated robot's control loop, a virtual force model is defined to describe the interaction profile and to correct the robot's motion trajectory in real time. The proposed human motion prediction algorithm acts as a feedforward model to update the robot's motion and to revise this motion in the process of human-robot interaction (HRI). The convergence of this method is analyzed theoretically. Comparative studies demonstrate the enhanced performance of the proposed approach.
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Publication status
- Published
File Version
- Accepted version
Journal
IEEE Transactions on Automation Science and EngineeringISSN
1545-5955Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Page range
1-8Department affiliated with
- Engineering and Design Publications
Notes
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2021-09-09First Open Access (FOA) Date
2021-09-09First Compliant Deposit (FCD) Date
2021-09-08Usage metrics
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